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대학생의 CCTV 체감안전도에 대한 영향 요인

Influencing Factors on Perceived Safety of CCTV among College Students

  • 오진환 (수원과학대학교 간호학과)
  • Jin-Hwan Oh (Department of Nursing, Suwon Science College)
  • 투고 : 2023.07.15
  • 심사 : 2023.08.28
  • 발행 : 2023.08.31

초록

본 연구의 목적은 범죄피해에 대한 두려움, 지역사회 내 사회적 무질서, 물리적 무질서, CCTV에 대한 체감안전도 변수 간의 상관성을 확인하고, CCTV에 대한 체감안전도의 영향요인을 살펴보는 데 있다. 연구대상자는 H시에 소재한 1개 대학교의 학생 140명으로, 2022년 06월 17일~2022년 08월 25일까지 설문조사를 하였다. 자료분석은 SPSS 23.0 program을 이용하여 기술통계량, Pearson's correlation, Stepwise multiple regression으로 분석하였다. 연구결과 범죄피해에 대한 두려움은 지역사회 특성 중 사회적 무질서, 물리적 무질서, CCTV에 대한 체감안전도와, 사회적 무질서는 물리적 무질서, CCTV에 대한 체감안전도와, 물리적 무질서는 CCTV에 대한 체감안전도와 상관성이 있었다. CCTV에 대한 체감안전도의 영향요인은 범죄피해에 대한 두려움과 사회적 무질서로 나타났으며, 수정된 결정계수(Adjusted R2)는 .572로 설명력은 57.2%이었다. 결론적으로 범죄피해에 대한 두려움과 사회적 무질서 인식개선을 통해 CCTV에 대한 체감안전도를 높이는 방안이 필요하다.

The purpose of this study was to examine the influencing factors of perceived safety for CCTV(Closed Circuit Television), and to confirm the correlation between fear of crime, social disorder, physical disorder in the community, and perceived safety for CCTV. Subjects were 140 students from one college located in H city using survey from June 17, 2022 to August 25, 2022. Data was analyzed by descriptive statistics, Pearson's correlation, and Stepwise multiple regression using the SPSS 23.0 program. As a result of the study, fear of crime was correlated with social disorder, physical disorder among community characteristics, and perceived safety of CCTV. Also, social disorder among community characteristics was correlated with physical disorder, perceived safety of CCTV, and physical disorder was correlated with perceived safety of CCTV. The factors affecting perceived safety for CCTV were fear of crime and social disorder, and the explanatory power was 57.2%(Adjusted R2=.572). In conclusion, it is necessary to improve the perceived safety of CCTV by improving the awareness of fear of crime and social disorder.

키워드

과제정보

이 논문은 2022년도 정부(과학기술정보통신부)의 재원으로 지원을 받아 수행된 연구임(No. 2021-0-00172, 감시카메라 기반 마스크 착용자 얼굴인식 및 재인식(Re-ID) 기술 개발)

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