Ⅰ. Drowning accidents caused across the world by rip currents
Japan has approximately 35,000 km of ocean coastline. More than 20 million people visit the 1,250 beaches across the nation and enjoy swimming in the summer season. However, every year, many drowning accidents occur, and precious lives are lost. About 1,300 to 1,600 drowning accidents occur in Japan each year, and about 1,500 to 2,000 people drown (National Police Agency, 2020). Rip currents are responsible for 45% of these drowning accidents (Ishikawa et al., 2014). Rip currents (often called “rips” or “rip tides”) are strong, narrow seaward flows arising from alongshore variations in wave setup landward of the breaker zone. Due to their dependence on wave breaking, rips can develop in any beach environment in oceanic, sea, and lacustrine environments (Houser et al., 2017). There are many drowning accidents caused by rip currents in foreign countries. More than 50% of drowning accidents reported in Australia, the United States, and the United Kingdom, were caused by rip currents (Brighton et al., 2013). Therefore, it is necessary to prevent these accidents on a global scale.
Ⅱ. Efforts to prevent drowning accidents caused by rip currents
Morgan, Ozanne-Smith, and Triggs (2009) found that gender, age, alcohol consumption, overconfidence in swimming ability, and lack of knowledge about rip currents, are associated with drowning accidents by rip currents. Caldwell et al. (2013) and Brannstrom et al. (2014), showed beachgoers pictures of rips and asking them to identify the area of the currents, reported that most of them misidentified the area. Warning signs are put up at many beaches to inform people of rip currents (Ménard et al., 2018). In addition to warning signs, in many jurisdictions flags are used to indicate lifesaving surveillance areas, safe swimming areas, or rip currents and other hazards. However, previous studies evaluating the effectiveness of warning signs, indicated that less than half the beachgoers were not aware of signs posted on the beach ( Matthews, Andronaco, & Adams, 2014; Brannstrom et al., 2015; Kaminski et al., 2017). It has also been reported that many people did not prepare for or avoid rip currents, even if they were aware of the warning signs ( Siegrist & Gutscher, 2006; Karanci, Aksit, and Dirik, 2005; Hall & Slothower, 2009). Furthermore, there are several problems associated with the usage of beach flags. As the color of the flag and its intended meaning differs from country to country, beachgoers from other countries may not be sure of the intended meaning (Ménard et al., 2018). Though lifesavers need to understand topographical features before finding rip currents, it is difficult to indicate the exact area through beach flags (Shimada, Ishikawa, & Komine, 2019). Furthermore, not all beaches are managed by lifesavers or beach flags, and beach flags cannot be set up outside the managed areas. Consequently, there is a possibility that beachgoers may believe that an area is safe and get caught in rip currents that are in areas that are not being managed.
Hatfield et al. (2012) and Houser et al. (2017) suggest that when beachgoers are given sufficient visual information about where rip currents occur, they can identify the area and are more likely to avoid these areas based on their observations. In Australia, lifesavers check the area for rip currents and other dangers, and inform beachgoers by sharing information through a smartphone app (MashableAsia, 2017). However, as the information is fed in at a predetermined time, it is not possible to track the constantly changing situation. In Japan, a new system using IoT has been developed that automatically detects the occurrence of rip currents through AI, and the information is displayed on a digital signage installed at the beach to alert beachgoers (Ishikawa et al., 2019). The advantage of this approach is the ability to display real-time alerts of geographically and temporally changing rip currents regardless of the area and time of the day. Endo et al. (2019) examined the awareness of beachgoers with the use of this approach. Based on a survey of 142 beachgoers, it was reported that more than 90% of them identified rip currents and tried to avoid the area.
Based on the above, it can be deduced that beachgoers can perceive the danger and avoid rip currents by visualizing them.
Ⅲ. The effect of cognitive bias
As reported in a previous study (Endo et al., 2019), visualization of rip currents through AI is an effective method to prevent drowning accidents. However, the study did not consider the effect of beachgoer’s cognition of rip currents. Ménard et al. (2018) pointed out that beachgoers are affected by cognitive bias to avoid rip currents. Confirmation bias is the most common bias, which is the cognitive tendency to focus on evidence that supports one’s beliefs or decisions and to ignore evidence that disproves them. This bias can make people look for evidence that it is safe to swim (for example, there are other people in the sea, there are no waves) and ignore evidence that it is not safe to swim (for example, there are red flags and warning signs). Scaman (2017) asked participants to evaluate their decision to swim in the sea by showing them photos of beaches with different waves and different number of people. She reported that although there were rip currents, participants were more likely to enter the sea after seeing photos where people were in the sea than when they saw photos of the same beach without people. The results indicated the impact of confirmation bias, as people make decisions based on the presence and behavior of others, and not on wave conditions. Additionally, if the perception of fear is inadequate, people assume that “It won’t happen to me” and therefore they are safe and can take the risk (Slovic et al., 1981, 1987). This tendency to interpret and predict things according to their advantage and to estimate that their risk is lower than that of others is called optimism bias (Armor & Taylor, 2002; Klein & Weinstein, 1997). Optimism bias has been studied in health problems (for example, the possibility of contracting lifestyle-related diseases or infections). Most people are not afraid of drowning as swimming is considered to be a low fear activity with known risks (Slovic et al., 1981, 1987; Sandman, 1989). Therefore, even if the danger of drowning by rip currents is mentioned, the danger is likely to be underestimated due to optimism bias.
Ⅳ. Purpose of the study
Various efforts have been made to prevent drowning accidents due to rip currents. However, there are has been no research on the effect of visualizing rip currents or the impact of optimism bias. Ménard et al. (2018) elaborated on the need for psychological studies to develop strategies to ensure that beachgoers avoid rip currents and prevent drowning accidents. This study investigates if the visualization of rip currents might assist in preventing drowning accidents, while taking into consideration the impact of optimism bias.