首页 | 本学科首页   官方微博 | 高级检索  
     


Intense classification training to increase the detection of drowning swimmers
Authors:Victoria Laxton  Christina J. Howard  Duncan Guest  David Crundall
Affiliation:Department of Psychology, Nottingham Trent University, Nottingham, UK
Abstract:Lifeguards engage in a continuous process of deciding whether swimmers are in danger or not. The variety of behaviours that distressed swimmers show makes it difficult to impart declarative knowledge to this effect during lifeguard training. As an alternative, we propose a novel training tool that requires novice participants to rapidly categorise 3-s video clips of real-life swimmers as either ‘safe’ or ‘drowning’. A control group also completed a sham intervention, with surfers that may ‘fall’. Due to the complex nature of swimming pools, a scaffolded training approach was employed, which gradually increased the amount of background information over subsequent training rounds. Results demonstrated that the drowning classification training improved responses in a subsequent drowning detection test, compared with the active control-group. The scaffolded approach appeared to prepare participants for processing swimmers in the drowning-detection test. The results provide a foundation for a novel training protocol to improve lifeguard skills.
Keywords:drowning detection  intense classification training  lifeguarding  visual processing  visual search
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号