• Korean Journal of Health Education and Promotion
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• v.26 no.5
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• pp.57-70
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• 2009

Objectives: This purpose of this study was to make clear the fitness to data of the causality model related to father's child-rearing participation in a double-income household. Methods: Subjects of this survey consisted of the fathers of 2,006 households that use 21 day-care centers and 4 kindergartens whose cooperation was received via the city government departments that have jurisdiction over day-care centers and kindergartens in cities A and B in prefecture I and in city C in prefecture II (city A: 499 households; city B: 1,113 households; city C: 988 households). The surveyed items consisted of the father's age, the father's educational history, the number of children, the age of the youngest child, the father's parental-role awareness, the father's daily working hours, the father's return-home time, and child-rearing participation by the father. Results: The fit indices were found to be CFI = 0.912, GFI = 0.948, and RMSEA = 0.082. Regarding the path coefficients, the path coefficient of the pathway from the age of the youngest child to the father's parent positivity (0.08) and the path coefficient of the pathway from the father's parent positivity to child-rearing participation (0.19) were both at statistically significant levels. Also, the father's return-home time and the working hours, which were considered as disincentives exhibited a direct effect on child-rearing participation without being influenced by the father's parent positivity or parent negativity. The path coefficient of the pathway from return-home time to child-rearing participation was -0.43, and the path coefficient of the pathway from working hours to child-rearing participation was -0.13. The value of the path coefficient expressing the relationship between the return-home time and working hours was 0.80. Conclusion: Authors infered that it'll be the basic material to build a generation mechanism about vanity and father's child-rearing participation appropriately as a result of this research.

• Korean Journal of Hospice Care
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• v.8 no.1
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• pp.13-28
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• 2008

Purpose: This paper aims to examine the subjective structures and types of school age children's perception of death through an investigative study on their perception of death in order to provide a basic material for them to understand death, and develop and carry out an effective death education program. Methods: The study method used the Q Methodology which can investigate the subjective structures and types of school age children's perception of death. For Q-population, 20 school age children were used as subjects for neutral interviews and open surveys, and through documentary research, a total of 132 statements were collected, For Q-samples, 23 statements (Q-samples) were derived through a non-structural method. P-samples were 31 school age children (8-13 year olds), Q-sorting was carried out using Q-cards, and the collected data was analyzed using the PC QUANL program. Results: As a result of the study, children's perception of death was divided into five types. The first type was functional type, characterized by prominent subjective perception regarding the elements of death, such as non-reversibility, universality, non-functionality, and causality. The second was after-life type, characterized by a strong, focus on life after death in one's perception of death, and it included children with Christian background and those who had experienced death in their immediate family. The third was religious type, characterized by a strong belief in being able to still watch over one's family and friends after one's death, resulting in a positive faith in the after-life. The fourth was fearful type, characterized by a deeper fear of death in comparison to other types. The fifth was realistic type, characterized by a strong and positive assent to the perception of good death. Conclusion: The significance of the results of this paper's study to Nursing is as follows. In terms of understanding the subjectivity of school age children's perception of death in nursing practice, and understanding the compositional elements of death presented with strong emphasis in existing literature and studies, the results will expand these understandings and allow us to understand the level of perception in school age children regarding the definition of death, after-life, and good death, be utilized as useful material in developing an effective death education program for them according to their type characteristics, and become the fertilizer for enabling the children to live a proper life and preventing the tendency to make light of death that occur in adolescence and the spread of suicides. In terms of nursing theory, the description and examination of the subjective structures and the characteristics of the different, types of school age children's perception of death can be utilized as useful material for building a model of school age children's perception of death, and be further used for teaching respect for life. In terms of nursing research, the results can contribute to research describing the effects of nursing intervention strategies and developing tools for providing psychosocial nursing in terms of giving school age children a positive perception of death according to their types as well respect for life.

• Journal of Venture Innovation
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• v.3 no.2
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• pp.41-76
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• 2020

This study confirmed factors affecting smart factory technology acceptance through empirical analysis. It is a study on what factors have an important influence on the introduction of the smart factory, which is the core field of the 4th industry. I believe that there is academic and practical significance in the context of insufficient research on technology acceptance in the field of smart factories. This research was conducted based on the Unified Theory of Acceptance and Use of Technology (UTAUT), whose explanatory power has been proven in the study of the acceptance factors of information technology. In addition to the four independent variables of the UTAUT : Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions, Government Assistance Expectancy, which is expected to be an important factor due to the characteristics of the smart factory, was added to the independent variable. And, in order to confirm the technical factors of smart factory technology acceptance, the Task Technology Fit(TTF) was added to empirically analyze the effect on Behavioral Intention. Trust is added as a parameter because the degree of trust in new technologies is expected to have a very important effect on the acceptance of technologies. Finally, empirical verification was conducted by adding Innovation Resistance to a research variable that plays a role as a moderator, based on previous studies that innovation by new information technology can inevitably cause refusal to users. For empirical analysis, an online questionnaire of random sampling method was conducted for incumbents of domestic small and medium-sized enterprises, and 309 copies of effective responses were used for empirical analysis. Amos 23.0 and Process macro 3.4 were used for statistical analysis. For accurate statistical analysis, the validity of Research Model and Measurement Variable were secured through confirmatory factor analysis. Accurate empirical analysis was conducted through appropriate statistical procedures and correct interpretation for causality verification, mediating effect verification, and moderating effect verification. Performance Expectancy, Social Influence, Government Assistance Expectancy, and Task Technology Fit had a positive (+) effect on smart factory technology acceptance. The magnitude of influence was found in the order of Government Assistance Expectancy(β=.487) > Task Technology Fit(β=.218) > Performance Expectancy(β=.205) > Social Influence(β=.204). Both the Task Characteristics and the Technology Characteristics were confirmed to have a positive (+) effect on Task Technology Fit. It was found that Task Characteristics(β=.559) had a greater effect on Task Technology Fit than Technology Characteristics(β=.328). In the mediating effect verification on Trust, a statistically significant mediating role of Trust was not identified between each of the six independent variables and the intention to introduce a smart factory. Through the verification of the moderating effect of Innovation Resistance, it was found that Innovation Resistance plays a positive (+) moderating role between Government Assistance Expectancy, and technology acceptance intention. In other words, the greater the Innovation Resistance, the greater the influence of the Government Assistance Expectancy on the intention to adopt the smart factory than the case where there is less Innovation Resistance. Based on this, academic and practical implications were presented.