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논문 기본 정보

자료유형
학술저널
저자정보
김유나 최정민 (건국대학교)
저널정보
한국주거환경학회 주거환경 住居環境 통권 제16권 제1호 (통권 제39호)
발행연도
2018.3
수록면
105 - 120 (16page)

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초록· 키워드

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Utilizing the big dataset extracted from a consumer injury surveillance system (CISS), this study extracted the most frequently occurred accident patterns at home and selected the interviewees who satisfied the criteria for in-depth interview. This paper is challenging from the perspective that combined the structured dataset from the CISS and the non-structured dataset from the in-depth interviews and utilized these two datasets to complement each other’s weak points so as to arrive at specific measures for preventing safety accidents within homes. From the association analysis of the structured CISS dataset, firstly, the greatest number of accidents in homes involves infants and the places where the accidents take place differ according to the children’s gender and age. Secondly, the major patterns of accidents indicate the types of accidents involving infants are more varied in boys than in girls, while in the 20 to 50 age group, women had a far more diverse pattern of accidents than men of the same age. From the unstructured in-depth-interviews with 10 respondents, firstly, kitchen and bathroom were not considered safe because they have a range of hazardous features, while the living room and bed room were also considered dangerous because of the nature of children’s activities in them. Secondly, some respondents had purchased and used safety devices in preparation for indoor safety incidents, but their appearance, hygiene, and performance left much to be desired and they needed to be used with caution. Thirdly, most respondents replied that information on life safety accidents and prevention of them was difficult to obtain and the specialized information was also inadequate. Therefore, it is urgent to establish an information delivery system related to the prevention of life safety accidents at home.

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Abstract
Ⅰ. 서론
Ⅱ. 이론적 고찰
Ⅲ. 소비자위해정보(CISS) 분석
Ⅳ. 심층인터뷰
Ⅴ. 결론
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UCI(KEPA) : I410-ECN-0101-2018-595-001916957