Objective: This article aims to identify factors that shape the knowledge, attitudes and behaviours of community residents in China's Heilongjiang province towards emergency preparedness. Findings of such a study may provide evidence to support the development of effective public risk communication strategies and education campaigns. Design: A cross-sectional household questionnaire survey was conducted in Heilongjiang province in 2014. A stratified cluster sampling strategy was employed to select study participants. The questionnaires were administered using face-to-face interviews. 2800 questionnaires were completed, among which 2686 (95.9%) were considered valid for data analyses. A multivariate logistic regression model was adopted to identify the extent to which the independent variables were associated with emergency preparedness. Results: Fewer than 5% respondents were well prepared for emergency. Over half (52%) of poorly prepared respondents did not know what to do in emergency; women (OR= 1.691), higher household income (OR ranging from 1.666 to 2.117), previous experience with emergency (OR= 1.552), higher levels of knowledge about emergency (OR= 2.192), risk awareness (OR= 1.531), self-efficacy (OR= 1.796), as well as positive attitudes towards emergency preparedness (OR= 2.265) were significant predictors for emergency preparedness. Neither educational attainment nor exposure to awareness-raising entered into the logic regression model as a significant predictor for emergency preparedness. Conclusions: The level of emergency preparedness in Heilongjiang residents is very low, which is linked with poor knowledge and attitudes of the residents towards emergency preparedness. Future emergency awareness campaigns should be more focused and tailored to the needs of intended audience, taking into consideration of their usual source of information and knowledge in relation to emergency.
[1]Harbin Med Univ, Sch Hlth Management, Harbin, Heilongjiang, Peoples R China;
[2]La Trobe Univ, Sch Psychol & Publ Hlth, Melbourne, Vic, Australia;
[3]Fudan Univ, Shanghai 200433, Peoples R China
(8.0+极速模式)