The Impacts of Narratives-based Risk Communication on Hazard Preparedness

Montana State University, Bozeman MT

Investigators

Abstract

Local hazard preparedness is vital to avoid disaster in the face of extreme events. Whereas conventional risk communication relies on scientific information to affect hazard preparedness, such technical information is often ineffectively assimilated into people's risk perceptions and decisions. Hazard preparedness is largely shaped by factors such as cultural values, cognitive biases, affect, knowledge, information, and experiences, all of which are communicated through stories that people construct and recount to one another. This research will test the effects of an innovative narrative-based risk communication strategy that locates science hazard information in locally produced hazard narratives. Effectively connecting scientific information to individual risk perceptions and decisions through co-produced risk narratives potentially offers an innovative way to improve hazard preparedness that could translate across hazard issues more broadly. With the project focus on flooding events, this research will draw upon expertise in social behavioral sciences, hydrology, and computer science. This interdisciplinary research effort focuses on testing whether a co-produced, narrative-based risk communication approach is more effective than conventional risk communication at improving hazard preparedness (defined as risk perception and decisions). The first objective is to develop co-produced risk narratives that are both scientifically accurate and locally relevant. Using a community-based participatory research (CBPR) approach, baseline data of flood risk narratives will be collected from river communities to ascertain narrative elements as identified in the Narrative Policy Framework (NPF). Narrative elements include subsets of narrative structure (e.g., use of characters, plot) and narrative content (who is cast in the roles of hero, villain, victim). Whereas narrative structures are stable, content varies across narratives. The characters cast in the narrative and their associated actions are formative in constructing different notions of reality and consequent decisions. Natural Language Processing computational techniques will then be used to identify key narrative content from the CBPR data to obtain the best set of combinations of narrative structure and narrative content situated in local language and images. Subsequently, researchers will quantify, explain, and depict sources of hydrologic uncertainty (data, model, and natural uncertainty) associated with flood frequency analysis in 100-year flood maps for each community. This resulting information will be embedded into the algorithmically enhanced CBPR-based risk narratives to create locally relevant and scientifically accurate flood risk narratives. These risk narratives will be returned to the CBPR groups for adjustment and validation. The second objective focuses on testing the effects of these co-produced risk narratives as narrative treatments on hazard preparedness (i.e., risk perception and intended decisions) with an experimental survey design across the larger population in these river communities. Differently constructed co-produced narratives (i.e., hero-focused, victim-focused, hero & victim focused narratives) will be used as treatments to test the extent to which they influence hazard preparedness in contrast to a non-narrative science statement and a control condition of no treatment. The findings are expected to provide insight into the power of narratives in communicating hazard risk and affecting hazard preparedness. The outcomes are expected to be useful for those local and federal entities involved in hazard preparedness strategies.