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Updated: Jul 14, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Assessing risk associated with recreational activities in coastal areas by using a bayesian network
Meng-Tsung Lee1, Yang-Chi Chang2, Han-Chung Yang1
1Department of Marine Leisure Management, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan.
Abstract:
Taiwan is an island and therefore has a considerable amount of coastal land. Drowning or near-drowning incidents often occur in coastal recreational areas. To reduce the risk of drowning or near-drowning associated with marine recreational activities in Taiwan, this study collected data on the risk associated with marine recreational activities. It selected risk factors using a modified Delphi panel method, with an expert panel used to obtain probability values for each risk factor. A Bayesian network for risk assessment was then established. The results of this study can serve as a reference for stakeholders involved in marine recreational activities. Severe weather conditions increase wave height and current speed, resulting in an increased risk of drowning or near-drowning when coastal recreational activities occur under these conditions. Individuals who undertake marine recreational activities without safety awareness are more likely to exhibit risky behaviors. When self-rescue ability is insufficient to prevent possible danger, the probability of drowning or near-drowning is higher. Serious incidents may lead to death, and therefore, marine recreational activities should be avoided when weather conditions are poor. In addition, the safety awareness and self-rescue ability of individuals undertaking coastal recreational activities should be improved. This study did not explore emergency response measures or postincident policy management.
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