• Journal of the Korean Society of Safety
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• v.16 no.3
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• pp.117-124
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• 2001

This paper introduces m analysis framework and procedure for the support of the cognitive error analysis of emergency tasks in nuclear poler plants. The framework provides a new perspective in the utilization of influencing factors into error prediction. The framework can be characterized by two features. First, influencing factors that affect the occurrence of human error me classified into three groups, i.e., task characteristic factors(TCF), situation factors(SF), and performance assisting factors(PAF). This classification aims to support error prediction from the viewpoint of assessing the adequacy of PAF under given TCF and SF. Second, the assessment of influencing factors is made by each cognitive function. Through this, influencing factors assessment and error prediction can be made in an integrative way according to each cognitive function. In addition, it helps analysts identify vulnerable cognitive functions and error factors, and obtain specific nor reduction strategies. The proposed framework was applied to the error analysis of the bleed and feed operation of nuclear emergency tasks.

• Journal of Service Research and Studies
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• v.5 no.2
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• pp.1-13
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• 2015

This study deduced an effect produced on the export performance of ICT company through precedent study. And the importance of each factor was analyzed, regarding the deduced influencing factors. And influencing factors in the export performance of ICT export companies were presented at a practical level on the basis of analysis results. According to the results of analysis, with regard to the influencing factor in the export performance of ICT company, companies' factors were interpreted as the most important influencing factor among the 1st hierarchical factors. According to the results of analysis after setting 12 factors for the 2nd hierarchical factor, 4 factors including export experience, CEO's market orientation, marketing strategy, and export market attractiveness were interpreted as very important factors. Therefore, it was possible to find that, with regard to the influencing factor in the export performance of ICT company, above all, enterprise internal factors- i.e., companies' factors, marketing factors- were more important influencing factors.

• Journal of the Ergonomics Society of Korea
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• v.31 no.5
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• pp.695-704
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• 2012

Objective: The purpose of this study was to investigate major factors influencing adoption of smartphone to promote its use by older adults. Background: Despite increasing proportion of elderly people and elderly market, the proportion of elderly smartphone user is still relatively small compared to whole smartphone users. Thus, we need to find out major factors influencing adoption of smartphone to increase proportion of elderly smartphone users. Method: Seven major factors were extracted from 36 survey questions using factor analysis. Regression analysis was also applied to determine specific factors affecting intention of use based on user versus non-user of smartphone, age, gender, and educational background. Results: As results of factor analysis and regression analysis, major factors influencing adoption of smartphone for elderly users were significantly different according to gender, age, educational background based on smartphone users or non-users. Conclusion: The result of this study identified major factors influencing adoption of smartphone for the elderly and provided basic information related to adoption of smartphone according to elderly people's characteristics. Consequently, we can expect to reduce the information gap and to improve quality of life for the elderly. Application: The development and marketing strategy could be applied differently based on the factors influencing adoption of smartphone. It is also possible to develop a prediction model for smartphone adoption according to elderly users' characteristics.

• Health Policy and Management
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• v.25 no.1
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• pp.31-39
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• 2015

Background: The purpose of this study is comparison of the results between regression and multi-level analysis to find out factors influencing outcome indicators (in-hospital death, length of stay, and medical charges) of stroke patients. Methods: By using patient sample data of Health Insurance Review & Assessment Service, patients admitted with stroke were selected as survey target and 15,864 patients and 762 hospitals were surveyed. Results: For the results of existing regression analysis and multi-level analysis, models were assessed through model suitability index value and as a result, the value of results of multi-level analysis decreased compared to the results of regression, showing it is a better model. Conclusion: Factors influencing in-hospital death of stroke patients were analyzed and as a result, intra-class correlation (ICC) was 13.6%. In factors influencing length of stay, ICC was 11.4%, and medical charges, ICC was 17.7%. It was found that factors influencing the outcome indicators of stroke patients may vary in every hospital. This study could carry out more accurate analysis than existing research findings through analysis of reflecting structure at patient level and hospital level factors and analysis on random effect.

• Journal of Korean Academic Society of Home Health Care Nursing
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• v.27 no.2
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• pp.156-168
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• 2020

Purpose: This study aimed to examine factors influencing health-related quality of life (HRQOL) and compare them between young-aged and old-aged patients with cancer. Methods: Data of 291 patients (young-aged: 168, old-aged: 123) were obtained from the 10th wave of the 2015 Korea Health Panel Survey. The HRQOL was measured using the Korean version of Euro-QoL-5D. Independent t-test, analysis of variance, and multiple regression analysis were performed to identify factors influencing HRQOL. Results: The average HRQOL score was 0.87±0.10 and 0.82±0.15 among young-aged and old-aged, respectively. The factors differed partially between the two groups. For young-aged, the influencing factors were activity restriction, subjectively perceived health status, and smoking. For old-aged, the influencing factors were activity restriction, subjective health status, and unmet healthcare needs. Conclusion: Strategies to improve the HRQOL of elderly adults need to be developed considering the age group. Additionally, studies that include clinical factors such as symptoms are required to prepare need-based practical approaches for better quality of life of such patients.

• Human Ecology Research
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• v.52 no.3
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• pp.213-228
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• 2014

This study examined the effects of peer relationships, depression, and aggression on bullying and victimization among boys and girls. The subjects were 364 3rd grade students (boys, 218; girls, 146) and 368 6th grade students (boys, 186; girls, 182), that is, a total of 732 students from three elementary schools. Data were collected on bullying, victimization, peer relationships (mutual friendship, mutual antipathy, and peer popularity), depression, and aggression (overt aggression and relationship aggression) from July 12, 2012 to July 13, 2012. These data were analyzed by means of a chi-squared analysis, t-test, and a logistic regression analysis. The results revealed that there were differences by sex in the case of direct bullying and victimization but no differences in the case of indirect bullying and victimization. Among boys, the factors influencing direct bullying were depression and overt aggression, and the factor influencing direct/indirect victimization was depression. Among girls, the factors influencing direct bullying were mutual antipathy relations and relational aggression, the factors influencing indirect victimization were mutual antipathy relations and peer popularity, the factor influencing indirect bullying was mutual antipathy relations, and the factor influencing indirect victimization was peer popularity. The results of this study showed that the factors influencing bullying and victimization are differences in sex. Finally, the implications and methodology for developing bullying prevention education programs were discussed.

• Korean Journal of Health Education and Promotion
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• v.31 no.5
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• pp.45-58
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• 2014

Objective: The purpose of this study was to analysis the determinants and trend of suicidal ideation the elderly in Korea. Methods: This study participants were selected the elderly over the age of 55 from the Korea National Health and Nutrition Examination Survey in 2001(n=1,122), 2005(n=2,098), and 2010(n=2,402). Statistical analysis methods used in this study were $x^2$-test, logistic regression analysis and other basic statistics such frequency, percentage using SPSS version 21.0. Results: In 2001, the influencing factors of suicidal ideation was spouses, subjective health status and stress recognition. In 2005, the influencing factors of suicidal ideation were spouses, subjective health status, chronic disease amount, activity limitation, depression experience and stress recognition. In 2010, the influencing factors of suicidal ideation were elderly, education level, subjective health status, activity limitation, depression experience and stress recognition. Conclusions: The health education considering the characteristics of each elderly group should be developed and applied to prevent adults' suicidal ideation because the factors influencing suicidal ideation were revealed differently between the elderly group.

• Journal of Service Research and Studies
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• v.6 no.1
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• pp.17-28
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• 2016

This study deduced an effect produced on organizational commitment of ICT Industrial workers through precedent study. And the importance of each factor was analyzed, regarding the deduced influencing factors. And influencing factors on organizational commitment of ICT Industrial workers were presented at a practical level on the basis of analysis results. According to the results of analysis, social support factors were interpreted as the most important influencing factor among the 1st hierarchical factors. According to the results of analysis after setting 12 factors for the 2nd hierarchical factor, 3 factors including emotional support, Informational support, and Substance/instrumental support, were interpreted as very important factors. However, psychological empowerment was analyzed to a relatively less critical.

• Child Health Nursing Research
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• v.23 no.1
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• pp.10-18
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• 2017

Purpose: The purpose of this study was to identify personal, contextual, and cognitive factors influencing the career preparation behavior of Korean nursing students. In this study, an examination was done of the fitness of a path model for the relationship among these factors based on the social cognitive career theory. Methods: The participants were 413 nursing students in South Korea. Data were collected using self-report questionnaires that included self-esteem, social support, self-efficacy, outcome expectation, career decision level, and career preparation behavior. Data were analyzed using descriptive statistics, Pearson correlation analysis, and path analysis. Results: The factors influencing career preparation behavior were self-efficacy, career decision level, self-esteem, outcome expectation, and social support. The factors influencing career decision level were self-efficacy, outcome expectation, self-esteem, and social support. Conclusion: The findings indicate that self-efficacy is an important factor influencing the career behavior of Korean nursing students. Nurse educators should consider personal, contextual, and cognitive factors of nursing students and develop systemic career guidance programs to help nursing students' career preparation behavior.

• Journal of Korea Technology Innovation Society
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• v.21 no.2
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• pp.522-559
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• 2018

In this study, we reviewed and analyzed the influencing factors of technology transfer performance in the previous studies (52 domestic journals and theses) and classified the various influencing factors into 6 top factors and 13 sub-factors based on the theoretical background. The study results of previous articles were analyzed by meta-analysis method so as to calculate the overall average effect size of influencing factors of technology transfer performance. As the result, the overall effect size (ESr) calculated through meta-analysis applying random effect model is .269, which corresponds to the medium effect size. By comparing effect sizes of influencing factors, the four(4) key influencing factors were also identified, which are 'number of researchers', 'dedicated organization', 'possess technology', and 'external cooperation'. The technology transfer performance are divided into three types: the number of technology transfers, technology transfer income, and other technology transfer performances. The major influencing factors of each type are derived through meta-analysis at the sub-category level. As moderator variables, the paper type and the data type were analyzed but no significant results were obtained. Since this research is limited to the technology transfer, it is necessary to carry out the study related to the influencing factors on the technology commercialization as following study.