Cognitive Load and Memory for Wireless Emergency Alerts

A Wireless Emergency Alert (WEA) is an emergency message sent directly to compatible phones through mobile carriers in the United States to inform the public of specific emergencies (natural disasters, severe weather, acts of terror, or child abduction) occurring in their vicinity. WEAs must convey relevant and comprehensive information to the public to be effective. Unfortunately, individuals are often already engaged in a task when they receive a WEA, which could lead to interference between the information contained in the WEA and information related to the ongoing task. This study examines how repetition of a WEA for a tornado warning can improve memory for message details and explores the cost associated with interruption and resource requirements of the ongoing task. For the primary task, participants engaged in a memory matching task that was interrupted by one tornado WEA or the same tornado WEA repeated three times (with a three-minute delay between each). Results indicate better memory for message information if it is repeated three times compared to once. The data also suggest that individuals may have more difficulty processing and retaining information related to the tornado warning if they are also engaged in a visual/spatial task. Given that it may not be possible to know what an individual will be doing when they receive a WEA, these results suggest that repetition could be used to reinforce emergency information comprehension. Future work will consider the effectiveness of multimodal messages on information recall and the potential cost associated with repetition. The current study can be used to advance current WEA communication techniques and increase public awareness during emergency events.

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Publication Details

Journal
AHFE international
Published
2025-01-01
DOI
https://doi.org/10.54941/ahfe1006589
Primary Topic
Context-Aware Activity Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Cognitive Load and Memory for Wireless Emergency Alerts

Mary Lynn Still, Hagar Baruch
AHFE international
Context-Aware Activity Recognition Systems
article

Cognitive Load and Memory for Wireless Emergency Alerts

Mary Lynn Still, Hagar Baruch
article en

Abstract

A Wireless Emergency Alert (WEA) is an emergency message sent directly to compatible phones through mobile carriers in the United States to inform the public of specific emergencies (natural disasters, severe weather, acts of terror, or child abduction) occurring in their vicinity. WEAs must convey relevant and comprehensive information to the public to be effective. Unfortunately, individuals are often already engaged in a task when they receive a WEA, which could lead to interference between the information contained in the WEA and information related to the ongoing task. This study examines how repetition of a WEA for a tornado warning can improve memory for message details and explores the cost associated with interruption and resource requirements of the ongoing task. For the primary task, participants engaged in a memory matching task that was interrupted by one tornado WEA or the same tornado WEA repeated three times (with a three-minute delay between each). Results indicate better memory for message information if it is repeated three times compared to once. The data also suggest that individuals may have more difficulty processing and retaining information related to the tornado warning if they are also engaged in a visual/spatial task. Given that it may not be possible to know what an individual will be doing when they receive a WEA, these results suggest that repetition could be used to reinforce emergency information comprehension. Future work will consider the effectiveness of multimodal messages on information recall and the potential cost associated with repetition. The current study can be used to advance current WEA communication techniques and increase public awareness during emergency events.

AHFE internationalVol. 189
Openalex Percentile: Top 87%
Context-Aware Activity Recognition Systems
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