Municipal Risk Communication and Public Trust: Reducing Counterproductive Behaviors Across Emergency Scenarios

Moran Bodas et al.

Risk Analysis2026https://doi.org/10.1111/risa.70232article
AJG 4
Weight
0.50

What the paper says

Municipal authorities play a critical role in risk communication, yet little is known about how their messages influence public safety behavior. This study examined how municipal informational messages shaped behavioral intentions across five emergency scenarios (wildfires, flooding, hazardous materials, extreme weather, and civil unrest) in a representative sample of 1509 adults. Using a cross-sectional experiment, we compared participants exposed to rumors alone versus rumors with municipal guidance. Results show that municipal messaging significantly reduced counterproductive behaviors such as rumor-spreading and convergence on hazard sites, though it had limited effects on preparedness and proactive information seeking. Trust in national authorities remained stronger than in local governments, and demographic factors such as gender, age, and political orientation moderated behavioral responses. These findings extend established models of risk communication by highlighting the contextual role of municipal authorities and suggest that local communication strategies are best framed as harm-reduction tools. The study underscores the need for scenario-specific message design, proactive trust-building, and future field-based research to capture real-world behaviors.

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https://doi.org/https://doi.org/10.1111/risa.70232

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@article{moran2026,
  title        = {{Municipal Risk Communication and Public Trust: Reducing Counterproductive Behaviors Across Emergency Scenarios}},
  author       = {Moran Bodas et al.},
  journal      = {Risk Analysis},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1111/risa.70232},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.