Paper No. 1
Presentation Time: 8:05 AM
OPTIMIZING IMMINENT THREAT MOBILE ALERTS TO MOTIVATE PROTECTIVE ACTION
The Wireless Emergency Alert (WEA) service was established following the WARN Act, and became available in April 2012. This new service allows customers who own WEA enabled wireless telephone models and other mobile devices to receive geo-targeted, text-like messages alerting them of imminent threats occurring in the area where they are physically located. Although much has been learned about full-text public warning messages, less is known about how to write effective short messages for mobile devices. This knowledge gap is further complicated by lack of understanding of the role text messages play in modern public warning systems. Funded by the U.S. Department of Homeland Security and the Federal Communications Commission, this research sought to determine how the contents of imminent threat WEA messages delivered over mobile communication devices can be optimized to motivate people to take protective action. Research questions included the following: How familiar is the public with the WEA system? How does the effectiveness of brief messages compare to longer messages? What is the most effective way to order the information contained in a brief message? What is the most effective single message source? What is the relative importance of different types of message content? Is it more effective to include a map along with text information? Would it be effective to include a URL along with text information? These questions and more were addressed in a series of eight experiments. Experiment findings were then validated in a household telephone survey of individuals who were in the city of Boulder during the 2013 Boulder Creek flood. Random digit dialing was used to recruit a representative sample of city residents (N=597); oversampling was used to recruit a second sample of residents who received the initial WEA message delivered over a mobile communication device (N=496). Data analysis was theory based, drawing on the warning literature and risk communication theory. Statistical methods included multiple linear regression to compare outcomes for different messages while controlling for selection factors. The project's findings will be discussed, including actionable guidance and considerations for optimized message contents of imminent threat alerts delivered over mobile communication devices.