Persuasion Illustrated: Motivating People to Undertake Self-Protective Measures in Case of Floods Using 3d Animation Focused on Components of Protection Motivation Theory 1. Introduction

SSRN Electronic Journal(2022)

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摘要
This study examines whether motivation to take protective measures in the case of flood risk can be increased using 3D-enhanced messages that emphasize various components of the protection motivation theory (PMT). It also tests the ability to memorise self-protective actions and the assumptions of PMT -including the processing of perceived risk. The study involved a field experiment implemented as a computer-assisted web interview (CAWI) with video material. We divided the subjects (n=740) into six groups; each watched a 3Denhanced alert message that informed the flood risks and listed recommended countermeasures. The messages differed in 3D animations illustrating selected components of PMT. Warning messages illustrating selected components of PMT were more effective in motivating subjects to act compared to the base condition; however, this was not the case when the messages focused on the probability of threat. Additional visualisations in the messages did not impair the subjects' ability to recall self-protective actions. Using an augmented PMT model with the interdependence of the threat and coping appraisal process leads to a significant improvement in fit. Warning messages are more effective in motivating people to act if they are accompanied by additional persuasive communication based on PMT (i.e. low cost of taking action, the efficiency of this action, self-efficacy, threat severity). Focusing only on threat probability is ineffective. Additionally, messages conveying only what protective measures participants should take should be avoided, because people tend to perceive the cost of action as too high and this weakens their intentions to perform it.
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关键词
Risk communication, Flood threat, 3D-enhanced warning, Visualizing persuasion, Personal safety measures, Protection motivation theory
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