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Why do people not prepare for disasters? A national survey from China

Political Science

Why do people not prepare for disasters? A national survey from China

Z. Han and G. Wu

This research by Ziqiang Han and Guochun Wu delves into why disaster preparedness actions remain largely unadopted in China. Despite various protective measures, research reveals that many citizens are hindered by misinformation and accessibility issues. The study underscores the importance of government trust and socioeconomic factors in enhancing community preparedness efforts.

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Playback language: English
Introduction
Natural disasters cause significant loss of life and economic damage globally, with an increasing trend fueled by climate change. Pre-disaster preparedness is crucial for mitigation. This study addresses the gap in understanding why people do not engage in specific preparedness actions. Two main conceptualizations of preparedness exist: a broad framework encompassing all disaster management phases, and a more focused approach emphasizing community knowledge and capacity building. Households are central to successful preparedness. Existing research, primarily using social-psychological paradigms and surveys, examines preparedness through material, awareness, and behavioral aspects, often employing theoretical frameworks such as the PADM, HBM, SCM, ToPB, and PMT. Influencing factors commonly studied include socioeconomic characteristics, hazard exposure, and trust in stakeholders.
Literature Review
The literature suggests that factors influencing household preparedness fall into four categories: socioeconomic and demographic characteristics (income, education, gender), hazard and contextual factors (environmental cues, place attachment, past disaster experience), psychological factors (risk perception, responsibility attribution, trust), and social factors (community engagement, support networks). Previous studies have shown mixed results regarding the influence of factors like gender, age, and disaster experience on preparedness behaviors, highlighting the need for further investigation. The Protective Action Decision Model (PADM) provides a sophisticated framework, but the transition from intention to action remains understudied, particularly concerning the adoption of protective actions during emergencies.
Methodology
A national survey in China collected data from 6530 respondents across all 31 provinces using stratified and quota sampling methods. Data collection occurred via an online platform between August and September 2018, with 81 incomplete or rushed responses excluded. The survey measured seven preparedness actions: preparing emergency supplies, paying attention to disaster information, having an emergency plan, knowing the nearest shelter, understanding building codes, participating in drills, and volunteering for emergencies. Responses were coded as "yes" or "no." Nine reasons for not adopting specific actions were provided, alongside an "other" option. Controlled variables included demographic and socioeconomic factors, disaster experience (natural disasters, H1N1, relocation due to disasters), and trust in government. Data analysis used multilevel linear and logistic regression models to examine the relationships between influencing factors and preparedness actions, controlling for province differences. Statistical software Stata 16.0 was utilized. The study adhered to the Declaration of Helsinki and received ethical approval.
Key Findings
Descriptive analysis revealed that a majority of respondents engaged in some preparedness activities, but significant gaps existed. The top three reasons for not engaging in preparedness were lack of awareness, difficulty accessing resources, and perceiving the actions as unnecessary. Multilevel regression analysis revealed that higher socioeconomic status, being male, being married, and living in urban areas were positively correlated with higher preparedness levels. Having elders in the family and living in rural areas were negatively correlated. Relocation due to prior disasters was positively associated with preparedness. Trust in government was also a significant positive predictor of preparedness. Further logistic regressions showed that higher socioeconomic status, relocation experience, trust in government, and urban residence were positively associated with all seven preparedness actions. However, the influence of other variables, such as gender, age, and disaster experience, varied across actions. For instance, having elders in the household was negatively correlated with several actions, while education showed mixed correlations.
Discussion
The findings demonstrate that lack of awareness, limited access to resources, and perceived inefficacy are major barriers to disaster preparedness in China. The study’s national scope offers valuable insights into the Chinese context, emphasizing the need for targeted community outreach and public education initiatives. The positive correlation between trust in government and preparedness highlights the importance of effective risk communication and building public confidence in government response capabilities. The mixed effects of disaster experience suggest that measuring disaster impact needs careful consideration, differentiating between minor and severe impacts. The study complements existing research by providing detailed reasons for inaction, refining our understanding of preparedness barriers.
Conclusion
This study provides valuable insights into the factors influencing disaster preparedness in China. The primary barriers identified—lack of awareness, resource access, and perceived inefficacy—underscore the need for improved public education, resource accessibility, and effective risk communication strategies. Future research should explore causal relationships through longitudinal or experimental studies, investigate specific barriers for diverse populations, and integrate geographical data for a more comprehensive understanding.
Limitations
The cross-sectional design limits causal inferences. Future research using longitudinal or experimental designs is needed to establish causality. The lack of geo-referenced data limits spatial analysis. Future studies should integrate geo-data to understand spatial variations in preparedness.
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