• Journal of The Korean Society of Integrative Medicine
• /
• v.8 no.4
• /
• pp.231-239
• /
• 2020

Purpose: The purpose of this study is to identify the relationship of between social support, emotional intelligence, depression, and health promotion behaviors of nursing college students, and to establish basic data for the development of a nursing intervention program for health promotion behaviors. Methods: This descriptive correlation study examined the correlation between the social support, emotional intelligence, depression, and health promotion behaviors of nursing students. 203 nursing college students located in J city participated in the study from November to December 2019. The collected data was analyzed used the SPSS WIN 22.0 program. The general characteristics of the subjects were analyzed by frequency and percentage, and health promoting behavior, social support, emotional intelligence, and depression were analyzed using mean and standard deviation. In this study, the correlation between the subjects' social support, emotional intelligence, depression, and health promotion behaviors was analyzed using Pearson correlation coefficient. Results: The study results showed that the subjects' health promotion behaviors averaged 2.22±0.38 points out of 4d social support averaged 3.83±0.59 points out of 5, emotional intelligence averaged 4.53±0.73 out of 7, and depression averaged 0.49±0.42 points out of 2 points. The analysis results of correlation between the subject's health promotion behaviors, social support, emotional intelligence, and depression showed that health promotion behaviors and social support (r=.287, p<.001), health promotion behaviors and emotional intelligence (r=.450, p<.001), and social support and emotional intelligence (r=.450, p<.001) had a positive correlation, but depression and health promotion behaviors (r=-.453, p<.001), depression and social support (r=-.259, p<.001), and depression and emotional intelligence (r=-.322, p<.001) had a negative correlation. Conclusion: This study will provide the basic data for a follow-up researches on the social support, emotional intelligence, depression and health promotion behaviors of nursing college students. It is expected to serve as the basic data for developing nursing intervention programs for health promotion behaviors in the future.

• Korean Journal of Radiology
• /
• v.24 no.9
• /
• pp.821-824
• /
• 2023

• The Korean Journal of Food & Health Convergence
• /
• v.7 no.2
• /
• pp.25-35
• /
• 2021

The purpose of study is to study the influence of elderly's family harmony reflects on suicidal tendency among the mental health. The study was a survey of 323 elderly people aged 65 years or older in the elderly welfare center located in S city. The variables of this study consisted of the independent variable emotional intelligence, the dependent variable suicide tendency and the mediating effect family harmony. As a result of the study. In the mediating effect of family harmony on the influence of emotional intelligence on suicidal thoughts, it was found that emotional intelligence had a positive (+) effect on family harmony (t=9.389, p<0.001), and emotional intelligence was related to suicidal thought It was found to have a negative (-) effect (t=-7.358, p<0.001). The mediating effect, family harmony, had negative (-) influence on suicidal thoughts (t=-3.956, p<0.001), and emotional intelligence also showed that suicidal thoughts had negative (-) influence (t=-4.828, p<0.001). In Conclusions, it was found that family harmony had a partial mediating effect on the influence of emotional intelligence on suicidal thoughts. Emotional intelligence, which can accept one's own emotions and feel the emotions of others in the position of others, is an important variable for family harmony.

• Child Health Nursing Research
• /
• v.13 no.4
• /
• pp.427-435
• /
• 2007

Purpose: This study presents the findings of various research on human intelligence and Multiple Intelligence Theory and suggested the implications of Multiple Intelligence Theory-based approach to the nursing education for the ill children. Method: Research objectives were accomplished by conducting a literature review. The main areas of the literature review included the Multiple Intelligence Theory, and it's application case for the children with learning disorder. Results: Dissatisfaction with traditional IQ tests has led to the development of a number of alternative theories, all of which suggest that intelligence is the result of a number of independent abilities that uniquely contribute to human performance. Among them, Multiple Intelligences Theory led to break intelligence down into at least eight different components: logical, linguistic, spatial, musical, kinesthetic, naturalist, intra-personal and interpersonal intelligences. In addition, Multiple Intelligence Theory and it's application case believes that every topic can be effectively taught and achieved using six entry points framework. Conclusions: The educational implications of Multiple Intelligence Theory in view of the health education and education in the children's hospital school should be considered for the ill children2's better education in a hospital setting.

• Journal of Korean Clinical Health Science
• /
• v.5 no.3
• /
• pp.915-924
• /
• 2017

Purpose. The purpose of this study was to investigate the influence of emotional intelligence, ego-resilience and communication competence in nursing students. Methods. Data was collected from a group of 146 nursing students by means of self reported questionnaires about emotional intelligence, ego-resilience and communication competence in nursing students from the period between February 18, 2017 to March 19, 2017. Results. There were positive correlations between emotional intelligence, ego-resilience and communication competence. Factors influencing the communication competence of nursing students were ego-resilience (${\beta}=.42$, p<.001), Academic achievement (${\beta}=.38$, p=.003)and emotional intelligence (${\beta}=.24$, p=.026). These factors explained 54.8% of the variance in the participants' communication competence (F=60.15, p<.001). Conclusions. In conclusion, strategies for increasing emotional intelligence and ego-resilience of nursing students' ego-resilience, should be developed to improve the communication competence of nursing students.

• Journal of the Korean Institute of Oriental Medical Informatics
• /
• v.20 no.1
• /
• pp.9-24
• /
• 2014

Purpose: This study was done to identify the relationship between emotional intelligence and nursing performance of clinical nurses in hospitals. Methods: Data were collected from a convenience sample of 396 nurses who work for a university in a city. The Questionnaire measured the level of emotional intelligence, nursing performance of nurses. The data were analyzed with PASW (SPSS) 18.0, using t-test, ANONA, Scheffe' test, Pearson correlation coefficients, and multiple regression. Results: The mean score of emotional intelligence was 3.44(${\pm}.39$), nursing performance was 3.59(${\pm}.42$). There were significant differences on emotional intelligence to age, education level, current position, total clinical career, job satisfaction. And there were significant differences on nursing performance to age, marital status, education level, current position, total clinical career, job satisfaction. It was significant positive correlation between emotional intelligence and nursing performance. The emotional intelligence and age explained 32.7% of variance in nursing performance. Conclusion: The findings indicate that to increase nursing performance, nursing managers need to develop emotional intelligence, especially use emotion and regulation of emotion for nurses.

• Journal of the Korea Convergence Society
• /
• v.13 no.1
• /
• pp.141-147
• /
• 2022

In a broad sense, the definition of digital health care is an industrial area that manages personal health and diseases through the convergence of the health care industry and ICT. In a narrow sense, various medical technologies are used to manage medical services to improve patient health. This paper aims to provide design guidelines so that artificial intelligence technology can be applied stably and efficiently to more diverse digital health care fields in the future by introducing use cases of artificial intelligence and machine learning techniques applied in the digital health care field. For this purpose, in this thesis, the medical field and the daily life field are divided and examined. The two regions have different data characteristics. By further subdividing the two areas, we looked at the use cases of artificial intelligence algorithms according to data characteristics and problem definitions and characteristics. Through this, we will increase our understanding of artificial intelligence technologies used in the digital health care field and examine the possibility of using various artificial intelligence technologies.

• Journal of Practical Engineering Education
• /
• v.16 no.4
• /
• pp.415-421
• /
• 2024

This study is a descriptive research study to understand the relationship between nursing professional intuition, artificial intelligence ethics, and digital health literacy of nursing college students. There was no difference in nursing professional intuition, artificial intelligence ethics, and digital health literacy according to the general characteristics of the subject. In addition, nursing professionals were found to have a significant positive correlation with artificial intelligence ethics consciousness and digital health literacy, and artificial intelligence ethics consciousness was found to have a significant positive correlation with digital health literacy. These results can be used as basic data for preparing educational programs that can strengthen digital health literacy capabilities by cultivating artificial intelligence ethics as well as nursing professionals of nursing college students.

• Journal of the Korean Society of School Health
• /
• v.28 no.3
• /
• pp.239-247
• /
• 2015

Purpose: The purpose of the study was to identify the effect of stress on the relations between emotional intelligence and burnout among nursing college students. Methods: The study is a cross-sectional survey and the participants were 363 students attending a nursing college located in Seoul. Data were collected by convenience sampling using self-reported questionnaires that consisted of general characteristics, emotional intelligence, perceived stress and burnout. Data were analyzed by descriptive statistics, t-test, ANOVA, correlation, and multiple regression. Results: Findings of the multiple regression were as follows. First, emotional intelligence had a significant negative-effect on stress. Second, emotional intelligence had a significant negative-effect on burnout. Third, stress had a significant positive-effect on burnout and had a mediating effect on the relationship between emotional intelligence and burnout. Conclusion: Results of the study suggest that as a way to reduce nursing college students' stress and burnout, programs which help improve nursing college students' emotional intelligence should be developed and implemented.

• Korean Medical Education Review
• /
• v.18 no.2
• /
• pp.47-50
• /
• 2016

Development of artificial intelligence is expected to revolutionize today's medicine. In fact, medicine was one of the areas to which advances in artificial intelligence technology were first applied. Recently, state-of-the-art artificial intelligence, especially deep learning technology, has been actively utilized to treat cancer patients and analyze medical image data. Application of artificial intelligence has the potential to fundamentally change various aspects of medicine, including the role of human doctors, the clinical decision-making process, and even overall healthcare systems. Facing such fundamental changes is unavoidable, and we need to prepare to effectively integrate artificial intelligence into our medical system. We should re-define the role of human doctors, and accordingly, medical education should also be altered. In this article, we will discuss the current status of artificial intelligence in medicine and how we can prepare for such changes.