One central goal of risk and crisis communication is to limit harm and minimize confusion during an event occurrence (Reynolds & Seeger, 2005). Unfortunately, often times during disasters and crises, it is necessary to communicate a message to an individual or group of individuals who are located in an area where it is unsafe, dangerous, or practically impossible to reach (Lachlan & Spence, 2007). For example, during an active shooter event, police and other first responders need to communicate with those still in danger, but often times cannot approach victims safely until they know enough about the situation – thus hindering efficient communication.
A similar need for communicating risk messages to individuals located in unsafe locations exists for weather disasters as well. During and even before disastrous weather events, important information must be communicated to specific populations located within the affected area to ensure the individuals will take proper safety measures or avoid risking their lives while removing themselves from an unsafe event. For example, during wildfires and similar weather events, firefighters and emergency responders are often tasked with going door-to-door to communicate evacuation orders or other beneficial information to the public. Yet, the nature of performing these processes frequently require that resources be redirected from attending to the disaster, or the situation is deemed unsafe for first responders to enter as well. Thus, new and innovative methods for disseminating this potentially life-saving information during crises and disasters are necessary.
Current alert systems offer emergency managers and practitioners a platform to disseminate messages in a time of need, and further developing and expanding these alerts can help reach additional populations. One such platform for communicating these risk-related messages are social robotics. During high involvement events, robotic delivery platforms have been useful for delivering messages regarding environmental risks and crises. Specific to weather, shelter-in-place warnings or storm shelters may be utilized, and encouraging first responders to enter these zones may be counter-intuitive dependent on the stage of the crisis. Similarly, many times during weather disasters, infrastructure which traditional media rely upon are damaged, requiring additional platforms to disseminate messages.
As humans and social robots increasingly interact (Levy, 2008), understanding how individuals process, retain, and utilize risk information is of importance to researchers. Recent research has suggested that humans are still more comfortable with a human-to-human interaction versus a human-to-robot interaction (Edwards, Edwards, Spence, & Westerman, 2016; Spence, Westerman, Edwards, & Edwards, 2014), but an argument can be made for a necessary level of anxiety during a risk or crisis situation (Lachlan, Spence, Rainear, Fishlock, Xu, & Vanco, 2016). Since risks and crises elicit a certain amount of anxiety themselves, and too much anxiety leads to counteractive behaviors (such as inactivity or antisocial behaviors; Lachlan & Spence, 2010), understanding how individuals perceive and interact with these platforms is integral to ensuring individuals are considering important risk messages in a time of need.
Methods:
To examine the aforementioned research questions, a six condition quasi-experiment will be conducted using one of two delivery platforms (robotic vs. face-to-face) to disseminate a risk message (a weather warning delivered using imperative only, declarative only, or both language structures). Approximately 200 undergraduate students will be recruited from a large university located in the Northeastern United States and brought into the laboratory to participate in the study. Upon entering the laboratory, students will be instructed by a laboratory assistant to take a seat near a window before beginning the study. Then, students will be delivered the randomly assigned risk message in the form of information derived from a mock severe thunderstorm warning, using imperative language, declarative language, or both. The warning message will either directly suggest students to move away from the window (imperative), mention that the National Weather Service suggests moving away from windows during severe thunderstorms (declarative), or contain both factual information and a suggested action (both condition). The warning message given by the robot will be identical in form to the message given in the face-to-face interaction, differing only in platform delivery.
The Lachlan & Spence (2010) Event Hazard/Outrage Scale will be used to evaluate perceptions of the threat posed by the risk and subsequent negative affective responses (fear, anger, etc.). Severity and susceptibility measures will be adapted from previous studies by the research team (Spence, Lachlan, Westerman, Lin, Gentile, & Sellnow, 2016), and will be used to further identify risk perceptions, as will measures of behavioral intention. Presence items adapted from the work of Lombard, Weinstein, & Ditton (2011) will be used to evaluate the extent to which participants felt socially present with the robot or individual conveying the risk message. To evaluate second-step perceptions of the agency issuing the warning, an adapted version of the RAND public health trust scale will be used (Eisenman, Williams, Gilk, Long, Plough, & Ong, 2012), along with Meyer’s (1988) source credibility index. Ten items in each condition will also be used to address the amount of factual information retained from the viewing experience; these items will be developed specifically for the current study.
Discussion:
The results from this study can help inform practitioners and emergency managers of some potentially useful practices during weather disasters. For example, if deploying a robotic platform into a weather disaster induces a large amount of uncertainty in some individual, robotic platforms may actually further inhibit behavior and lifesaving steps when necessary. On the contrary, if individuals appreciate receiving information during a dangerous moment, it may be useful to further explore this platform during disaster communication, to better redirect human resources where most necessary.
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