Examining quality information flow in rural communities during disasters: findings from community leaders in emergency response
Abstract
Effective risk communication during disasters depends not only on the availability of information, but on whether information is trusted, interpreted as credible, and acted upon under conditions of uncertainty. Rural communities face distinct challenges in this regard due to infrastructural constraints, close-knit social networks, and historical mistrust of formal institutions. This study examines how quality information flows are produced, evaluated, and contested during crises within rural communities, drawing on qualitative interviews with community-embedded emergency response leaders who occupy dual roles as both responders and residents. Guided by the Theory of Motivated Information Management and community resilience frameworks, we analyze how uncertainty, trust, and social relationships shape information seeking, evaluation, and dissemination during disaster response. Findings show that perceptions of information credibility hinge less on message content alone than on source trust, relational embeddedness, and transparency about uncertainty. While coordinated, multi-channel communication systems facilitate information flow, breakdowns in infrastructure and historical mistrust create conditions in which misinformation circulates through trusted informal networks. Building on these insights, we propose the Community-Embedded Information Evaluation Framework, which integrates strategic communication systems, infrastructure, interpersonal communication, and community relationships to explain how quality information flow emerges in rural crisis contexts. This framework advances risk communication scholarship by foregrounding trust, cultural competence, and relational dynamics as central to managing risk and misinformation during disasters.
Fields of Study & Subjects
Public Relations and Crisis Communication
Disaster Management and Resilience
Risk Perception and Management
Publication details
- Journal / source
- Journal of Risk Research
- Volume
- 29
- Issue
- 3
- Pages
- 376–390
- Publication date
- 3 March 2026
- Language
- EN