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Can the visualization of rip currents prevent drowning accidents? Consideration of the effect of optimism bias

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Abstract

Drowning accidents at beach in Japan are caused by rip currents. To reduce these accidents, a new technology that can detect rip currents and notify beachgoers by using the Internet of Things (IoT) and Artificial Intelligence (AI) was proposed. However, studies on the effect of visualizing rip currents or considering the effect of optimism bias have not been conducted. This study investigates if visualization of rip currents might help in preventing drowning accidents, while considering the effect of optimism bias. The participants were 90 Japanese beachgoers. They were asked to answer questions based on their knowledge of the beach and rip currents, their optimism bias regarding rip currents, and awareness with or without visualization. The results of the analyses suggest that despite optimism bias, the visualization of rip currents increases the tendency of beachgoers to perceive and avoid rip currents. As described above, it was found that by visualizing the rip current, beachgoers were able to perceive and avoid rip currents. In addition, an understanding of rip currents is positively related to the intent to avoid rip currents even when rip currents are visualized. Therefore, it is necessary not only to enhance the avoidance tendency by visualizing rip currents, but also to further enhance knowledge of beachgoers to deepen the understanding of rip currents including the danger associated and methods to avoid them.

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Acknowledgements

This study was supported by the Nippon Foundation and the Japan Lifesaving Association. The authors would like to thank Editage (https://www.editage.jp/) for English-language editing.

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This manuscript was funded by the Nippon Foundation.

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Correspondence to Shintaro Endo.

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This study was exempted by the ethics committee of the authors’ affiliated university (2018–5).

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Endo, S., Shimada, R., Ishikawa, T. et al. Can the visualization of rip currents prevent drowning accidents? Consideration of the effect of optimism bias. Nat Hazards 110, 2017–2033 (2022). https://doi.org/10.1007/s11069-021-05023-x

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  • DOI: https://doi.org/10.1007/s11069-021-05023-x

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