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Predicting Complete Mask Coverage During the COVID-19 Outbreak in Hong Kong Using the Health Belief Model.
Tam, Victor Chi Wing; Yip, Tyrone Tsz Yeung; Chan, Lisa Ho Lam; Khaw, May Ling; Man, Dickson Yik Lok; Chan, Abbie Mei Sin; Leung, Johnny Ka Chun; Ching, Jerry Chi Fung; Lee, Shara Wee Yee.
  • Tam VCW; Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
  • Yip TTY; Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
  • Chan LHL; Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
  • Khaw ML; Tasmanian School of Medicine, University of Tasmania, Hobart, TAS, Australia.
  • Man DYL; Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
  • Chan AMS; Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
  • Leung JKC; Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
  • Ching JCF; Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
  • Lee SWY; Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
Asia Pac J Public Health ; 35(4): 315-317, 2023 May.
Artículo en Inglés | MEDLINE | ID: covidwho-2304527
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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Estudio observacional / Estudio pronóstico Límite: Humanos País/Región como asunto: Asia Idioma: Inglés Revista: Asia Pac J Public Health Asunto de la revista: Salud Pública Año: 2023 Tipo del documento: Artículo País de afiliación: 10105395231167498

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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Estudio observacional / Estudio pronóstico Límite: Humanos País/Región como asunto: Asia Idioma: Inglés Revista: Asia Pac J Public Health Asunto de la revista: Salud Pública Año: 2023 Tipo del documento: Artículo País de afiliación: 10105395231167498