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Journal Article

Citation

Whitmer DE, Sims VK. Hum. Factors 2021; ePub(ePub): ePub.

Copyright

(Copyright © 2021, Human Factors and Ergonomics Society, Publisher SAGE Publishing)

DOI

10.1177/00187208211029444

PMID

unavailable

Abstract

OBJECTIVE: The goal was to examine the effectiveness of fear language in the protective action recommendation of an emergency warning, which instructs people how to prepare and stay safe.

BACKGROUND: Past work is limited because it has focused on describing the severity of the weather crisis, not improving the recommendation. Likewise, other research has examined fear appeals that overemphasize death, which leads to poor risk perceptions.

METHOD: In Experiment 1, the presence of fear language and second-person personal pronouns (i.e., "you") in a recommendation was manipulated. Experiment 2 examined how fear language and a hurricane changing in intensity influenced risk perceptions across three decision points.

RESULTS: Experiment 1 suggested that fear language was more influential than a pronoun on risk perceptions. Experiment 2 suggested that fear language in a protective action recommendation was most impactful in the case of a hurricane decreasing in intensity.

CONCLUSION: Protective action recommendations with fear language influence risk perceptions and behaviors. The magnitude of this influence is dependent on how people have categorized the hurricane (i.e., low vs. high risk). APPLICATION: These results demonstrate that fear appeals in hurricane warnings can be useful, especially in cases when a low to medium risk event is still extremely dangerous. Likewise, these results demonstrate a need for caution, as fear appeals are not a "one size-fits-all" approach to increasing risk perceptions and should be used thoughtfully. Recommendations of when to use fear appeals in protective action recommendations are provided based on the present data.


Language: en

Keywords

risk perception; emergency warnings; fear language; hurricanes; protective action recommendations; technology-based warnings

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