• 대한통합의학회지
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• 제8권4호
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• pp.231-239
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• 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
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• 제24권9호
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• pp.821-824
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• 2023

• 식품보건융합연구
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• 제7권2호
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• pp.25-35
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• 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
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• 제13권4호
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• pp.427-435
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• 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.

• 한국임상보건과학회지
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• 제5권3호
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• pp.915-924
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• 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.

• 대한한의정보학회지
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• 제20권1호
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• pp.9-24
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• 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.

• 한국융합학회논문지
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• 제13권1호
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• pp.141-147
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• 2022

디지털 헬스케어의 정의는 광의로는 헬스케어 산업과 ICT가 융합되어 개인건강과 질환을 관리하는 산업영역을 의미하고, 협의로는 환자의 건강을 향상시키기 위해 의료 서비스를 관리하는데 다양한 의료 기술을 사용하는 것을 포함한다. 본 논문은 디지털 헬스케어 분야에 적용되고 있는 인공지능과 기계학습 기법들의 활용사례 소개를 통해 다양한 디지털 헬스케어 분야에 인공지능 기술이 안정적이고 효율적으로 적용할 수 있도록 설계 지침을 제공하는 데 목적이 있다. 이를 위해 본 논문에서는 의료분야와 일상생활 분야로 나누어서 살펴보았다. 두 영역은 다른 데이터 특성을 갖는다. 두 개의 영역을 보다 세분화하여 데이터 특성 및 문제 정의 및 특징에 따른 인공지능 알고리즘 활용사례를 살펴보았다. 이를 통해 디지털 헬스케어 분야에서 활용되는 인공지능 기술들에 대한 이해도를 높이고 다양한 인공지능 기술의 활용에 대한 가능성을 검토하여 인공지능 기술이 헬스케어 산업과 개인의 건강한 삶에 기여할 수 있는 근본적인 가치에 대해 고찰한다.

• 실천공학교육논문지
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• 제16권4호
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• pp.415-421
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• 2024

본 연구는 간호대학생의 간호전문직관, 인공지능 윤리의식과 디지털 헬스리터러시의 관계를 파악하기 위한 서술적 조사 연구이다. C 지역의 간호학과 대학생 1-4학년 총 244명을 대상으로 수집된 자료는 SPSS 22.0 프로그램을 이용하여 빈도 분석, t-test, ANOVA, Pearson correlation coefficient 하였다. 그 결과, 간호전문직관 3.94±0.45점, 인공지능 윤리의식 3.37±0.43점, 디지털 헬스리터러시 3.15±0.29점이였다. 대상자의 일반적 특성에 따른 간호전문직관, 인공지능 윤리의식, 디지털 헬스리터러시에는 차이가 없는 것으로 나타났다. 또한 간호전문직관은 인공지능 윤리의식(r=0.39, p<.001)과 디지털 헬스리터러시(r=0.36, p<.001)와 유의한 정적 상관관계가 있었으며, 인공지능 윤리의식은 디지털 헬스리터러시(r=0.41, p<.001)와 유의한 정적 상관관계가 있는 것으로 나타났다. 이러한 결과는 간호대학생의 간호전문직관 뿐만 아니라 인공지능 윤리의식을 함양하여 디지털 헬스리터러시 역량을 강화시킬 수 있는 교육 프로그램 마련의 기초자료로 활용할 수 있을 것이다.

• 한국학교보건학회지
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• 제28권3호
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• pp.239-247
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• 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.

• 의학교육논단
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• 제18권2호
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• pp.47-50
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• 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.