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언어 네트워크 분석을 이용한 코로나19 위험인식과 예방행위에 관한 이해

Understanding public perception of COVID-19 and preventive behaviors based on a semantic network analysis

보건교육건강증진학회지 2020년 37권 4호 p.41 ~ 58
장사랑, 손애리,
소속 상세정보
장사랑 ( Jang Sa-Rang ) - Sahmyook University Department of Health Management
손애리 ( Sohn Ae-Ree ) - Sahmyook University Department of Health Management

Abstract


Objectives: This study aimed to explore the public perception of the coronavirus disease (COVID-19) and preventive behaviors by age group.

Methods: Focus group interviews were conducted, and response contents were classified by age group and analyzed. A semantic network analysis was employed to investigate relationships among keywords, and some sub-network characteristics were derived using a cohesive group analysis.

Results: Given the keywords and sub-networks derived from the semantic network analysis, COVID-19 risks were classified into three levels: individual, group, international. Preventive behaviors were classified into two dimensions (personal hygiene, distancing). It was also possible to visualize and confirm connections among detailed concepts that constituted the public perception of COVID-19.

Conclusion: This study shows that in establishing an effective crisis management response strategy to prevent emerging infectious diseases, biological risks and risk perception should be considered.

키워드

COVID-19; risk perception; Non-Pharmaceutical Interventions(NPIs); semantic network analysis; qualitative research

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